Is a long-run sustainability transition taking place or are countries just encouraging innovation in alternative energies in a short-run approach, given the conditions of fossil fuel markets? In this paper we a
Of course, logistic regression can also be used to solve regression problems, but it's mainly used for classification problems. Tip: Use machine learning software to automate monotonous tasks and make data-driven decisions. Another example would be predicting whether a student will be accepted into...
For this purpose, we examined how belonging to one of the four topic groups predicts the retweet count of the tweets (see Table 2). We used a negative binomial regression to account for the overdispersion of the dependent variable (retweet count). The predictors in the regression were dummy ...
Jeff Meyer is a statistical consultant with The Analysis Factor, a stats mentor for Statistically Speaking membership, and a workshop instructor. Read more about Jeff here.Poisson and Negative Binomial Regression for Count Data Learn when you need to use Poisson or Negative Binomial Regression in...
red is used to attract mates by primates, fish, and crabs (Östlund-Nilsson et al.2006; Baldwin and Johnsen2009; Rigaill et al.2019). Sticklebacks use red signals to defend territories (Kim and Velando2014). Red is also a powerful filial imprinting stimulus for domestic chicks (Salzen ...
Standardized regression coefficients remove the unit of measurement of predictor and outcome variables. They are sometimes called betas, but I don’t like to use that term because there are too many other, and too many related, concepts that are also called beta. There are many good reasons to...
Body-awareness is one of the fundamental modules of self-representation. We investigated how body-awareness could contribute to dogs' decision making in a novel spatial problem where multiple solutions are possible. Family dogs (N = 68) had to obta
What may remain incorrect for now is numpy.random functionality, because Cython 3.0 had a regression there that isn't fixed yet, and it doesn't seem possible to override __module__ at the moment. And numpy.random is the only submodule with Cython code. The changes will land in NumPy 2.2...
To analyze the influence of children age, mixed logistic regression was conducted in R including a random intercept (note that logistic regressions were preregistered but in hindsight the random intercept is necessary to account for dependency in the data54). Results showed a main effect for age ...
A Poisson or similar count model (quasi-Poisson, negative binomial) makes an assumption about the association between the value of a count and the variance in the count. That won't necessarily hold for this type of ranking data. It's quite possible to perform an ordinal regression with a ...